Using assembly representations to enable evolutionary design of Lego structures

This paper presents an approach to the automatic generation of electromechanical engineering designs. We apply messy genetic algorithm (GA) optimization techniques to the evolution of assemblies composed of LegoTM structures. Each design is represented as a labeled assembly graph and is evaluated ba...

Full description

Saved in:
Bibliographic Details
Published in:AI EDAM 2003-05, Vol.17 (2), p.155-168
Main Authors: PEYSAKHOV, MAXIM, REGLI, WILLIAM C.
Format: Article
Language:English
Subjects:
Assembly lines
Assembly Modeling
Chromosomes
Computer science
Computer-Aided Design
Engineering Design
Engineering research
Evolutionary Design
Genetic Algorithms
Genetic engineering
Lego
Physical properties
Research methodology
Structural engineering
Studies
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper presents an approach to the automatic generation of electromechanical engineering designs. We apply messy genetic algorithm (GA) optimization techniques to the evolution of assemblies composed of LegoTM structures. Each design is represented as a labeled assembly graph and is evaluated based on a set of behavior and structural equations. The initial populations are generated at random, and design candidates for subsequent generations are produced by user-specified selection techniques. Crossovers are applied by using cut and splice operators at the random points of the chromosomes; random mutations are applied to modify the graph with a certain low probability. This cycle continues until a suitable design is found. The research contributions in this work include the development of a new GA encoding scheme for mechanical assemblies (Legos), as well as the creation of selection criteria for this domain. Our eventual goal is to introduce a simulation of electromechanical devices into our evaluation functions. We believe that this research creates a foundation for future work and it will apply GA techniques to the evolution of more complex and realistic electromechanical structures.
ISSN:0890-0604
1469-1760
DOI:10.1017/S0890060403172046